Operations | Monitoring | ITSM | DevOps | Cloud

In order for users to get the most out of the data being sent to Sentry, it’s important that we make it easy to find that data. Our team works on features to help users browse their data to find a particular event using search queries and filters. The search bar enables users to find their data by specifying search terms. Searching uses the Sentry Search Syntax, which can be barrier for users.

Engineers ignore cloud costs because of broken feedback loops, not apathy. Learn what AI cost management is, why AEO matters more than ever, and how a cost management agent embeds accountability directly into engineering workflows. Engineers ignore cloud costs because cost data arrives too late and too disconnected from their workflow to act on.

An LLM gateway is a proxy that sits between your applications and model providers, handling routing, failover, caching, and cost controls through one API. The strongest picks in 2026: LiteLLM for self-hosted control, OpenRouter for instant multi-model access, Portkey for managed governance, and Bifrost for production-scale throughput. Enterprises spent $37 billion on generative AI in 2025, a 3.2x jump in one year, per Menlo Ventures.

ChatGPT Work has become a common starting point for data and product teams. Analysts open it to compare launch adoption across segments, diagnose a metric that moved overnight, or turn a week of scattered numbers into a readout that a leader can act on. But the moment teams ask whether their experiment actually caused an effect they’ve observed, the conversation stalls.

Australia’s home-grown global automated infrastructure platform is part of a cohort of companies with Australian operations that will provide regional businesses and institutions access to NVIDIA accelerated computing and NVIDIA Nemotron open models. It’s a point of pride for all of us at Megaport that we’ve built a global automated infrastructure platform while maintaining our deep Australian roots.

model-right-sizer-schema is a Claude Code skill that designs the typed contract between one agent and the controller that dispatches it. Point it at an agent plus its controller and it returns a JSON prescription with typed in/out fields, an exclusion list that keeps raw logs out of the reply, a before/after size delta, then writes the contract into the agent's own file. It picks from nine portable output-shape families, or your repo's own.

AI agents can help investigate failed builds, fix flaky tests and automate other development tasks. But setting up those agents has required more Pipelines configuration than it should. Agent-powered steps often need different compute, permissions and runtime settings from ordinary build and test steps. Until now, teams have either repeated those settings across every agent-powered step or tried to make one set of global defaults work for everything.